The present invention relates generally to energy reducing techniques, and more specifically to energy saving techniques used for reducing energy consumption of a building.
In modern society, buildings provide very important space for business activities. Most business activities happen in the buildings, such as business strategy planning, business negotiation, customer visit, software development, hardware design, etc. Providing a comfortable and inviting environment for occupants of the building is instrumental to improve their working efficiency and productivity, which however, necessarily requires provision of better illumination, air conditioning and ventilation. As a result, more energy is consumed.
Currently, buildings already consume considerable energy. It is estimated that buildings will become the largest consumer of global energy by 2025—more than the transportation and industrial sectors combined. Commercial and residential buildings will consume ⅓ of the worlds energy, wherein up to 50% of the electricity and water that is used by these buildings could be wasted. As a result, power grid load becomes heavier and heavier. Once any failure happens to the power grid, very serious loss will be caused to industrial and commercial fields.
Therefore, reducing the energy consumption of buildings while maintaining the safety and comfort for occupants is a key performance index (KPI) for estate managers; it also is the goal of many ongoing green buildings.
A current way to save energy is to use various sensors to monitor the environment of the building and control devices in the building on demand. For instance occupancy sensors can be used to detect the presence of people, i.e. if there is no people in an area, the illumination in the area will be maintained at a low level, while if people are detected, the illumination level will be increased, or temperature sensors can be used to monitor the environment temperature to control operation of the air conditioner and ventilator. Sensors are good at controlling devices in the field in real time, but they could not provide predictive planning information for building management system in advance.
Another way to save energy is to use an intelligent algorithm to analyze occupants' behavior in the building and thus extract their behavioral patterns. These patterns will be used to control the devices in the field. For example, sensors detect that people come to the office around 8:30 am every day, and a pattern can be extracted as “people are in their office starting at 8:30 am,” then the related control strategy could be expressed as “increasing the illumination level at 8:30 am, and turning on the air conditioner/ventilator at 8:15 am (a bit time advance to ensure the air will cool down at 8:30 am).” The advantage of this pattern analysis method is that it can capture the recurring activities in a building, and enable to predict operations of the building management system to some extent. However, such predictive operations are based on rules of thumb, therefore are not very accurate (precise), and cannot capture activities at more detailed levels, e.g., specific use patterns of meeting rooms, etc.
Therefore, a demand side management (DSM) method is proposed. FIG. 2 illustrates a schematic block diagram in which a building management system in the prior art manages electrical devices in a building based on a DSM request message from a smart grid. The demand side management is one of important technologies of the current smart grid. The basic idea of the demand side management is that the power grid can send a DSM signal to electrical devices connected thereto in the peak hour to inform them to lower load, and the electrical devices, upon receipt of the signal, should respond to the signal (i.e., lower the load), otherwise much higher fees will be charged for the amount of electricity consumed by these devices during the peak hour. Another possible situation is that if these devices do not respond to the DSM signal to lower the load, the power grid may become too overloaded and break down, which will cause very serious losses to business and industrial enterprises.
In the prior art of applying the DSM to the building management, the devices in the power grid respond to the DSM signal in an ad hoc manner, and thus it may not guarantee a total effect of the DSM, for example, the reduction of load might not meet a desired requirement so that the estate manager has to pay more electricity fees. Another possible way is centralized building management, wherein the building management system may uniformly reduce the load of all devices upon receipt of the DSM request. However, this way does not take differences between various business activities in consideration so that it cannot ensure quality of service for some important business activities. This might exert a negative influence on these business activities and cause irreparable losses.